Background Image
如何赢得灵罗娃娃与诡术妖姬的对抗赛灵罗娃娃 is in the b tier of champions

灵罗娃娃 vs 诡术妖姬

如何在LoL中以灵罗娃娃的身份击败诡术妖姬灵罗娃娃 is in the b tier of champions
FighterAssassin
AssassinMage

如何击败诡术妖姬成为灵罗娃娃

based on 1,232 灵罗娃娃 vs 诡术妖姬 matchups
胜率
50.8 %
kda
1.63
受欢迎度
1.5 %

How We Analyze LoL Champion Counters

We at MOBA Champion summarize millions of recently ranked League games each and every week. Within our data, 灵罗娃娃 engaged 诡术妖姬 1232 times. Including so many games with 灵罗娃娃 vs 诡术妖姬 provides us confidence in our capability to prepare useful data and a solid build to suppress 诡术妖姬. This counter matchup is somewhat rare. 灵罗娃娃 is forced to battle against 诡术妖姬 in only 1.5% of her matches.

灵罗娃娃 vs 诡术妖姬 Matchup Summary

灵罗娃娃 has done a average job of countering 诡术妖姬. Typically, she wins a acceptable 50.8% of the time the champs clash against each other in. In 灵罗娃娃 versus 诡术妖姬 games, 灵罗娃娃’s team is 0.1% less likely to earn first blood. This indicates that she probably won't be able to get first blood against 诡术妖姬.

counterTitle

物品

第一项

期望时间
多兰之盾生命药水

下一个项目

5分钟
反曲之弓恶魔法典

Core 灵罗娃娃 Items

22分钟
纳什之牙裂隙制造者影焰

可选项目

灭世者的死亡之帽星界驱驰海克斯科技火箭腰带中娅沙漏

Summoner Spells

summonerhaste summoner spell D
summonerteleport summoner spell F

技能顺序

为灵罗娃娃提升等级的第一个技能q
>
为灵罗娃娃提供的第二种能力,以提高水平e
>
灵罗娃娃 最大化的最后一项技能w

符文

精密征服者气定神闲传说:欢欣坚毅不倒
坚决复苏之风坚定
Attack SpeedAdaptive ForceArmor
灵罗娃娃's passive ability p
灵罗娃娃's q ability q
灵罗娃娃's w ability w
灵罗娃娃's e ability e
灵罗娃娃's ultimate ability r
1
Q
2
E
3
Q
4
W
5
Q
6
R
7
Q
8
E
9
Q
10
E
11
R
12
E
13
E
14
W
15
W
16
R

Guide to Countering 诡术妖姬 as 灵罗娃娃

Tips for Playing as 灵罗娃娃 against 诡术妖姬

格温仍然可以对她的圣霭外的敌人们造成伤害,例如她远距离的终极技能。

格温的有些技能可以对多个敌人施加她的被动技能,因此请瞄准敌人最扎堆的地方,来最大化伤害和治疗效果。

攻击不要停 - 格温的攻击除了造成额外伤害之外,还会强化或重置她的很多技能。

Advice to Win Against 诡术妖姬

- 乐芙兰的终极技能可以在她的技能施放期间,或是,少见地在一个遥远的位置创造一个假的乐芙兰。

- 在远处创造的假乐芙兰将会跑向距它最近的敌方英雄,施放一个无害的技能,随后立刻消失。

- 要先对乐芙兰发起攻击,来规避她的大部分小诡计,尤其是她在近期用过她的位移技能【魔影迷踪】时。

- 晕眩或沉默乐芙兰将阻止她激活【魔影迷踪】返回。

灵罗娃娃 vs 诡术妖姬 Counter Stats

灵罗娃娃 Image
winRate
50.8 %
VS
winRate
49.2 %
诡术妖姬 Image
5.8
< kills >
7.6
6.2
< deaths >
4.7
4.3
< assists >
6.2
1.32
< killingSprees >
1.66
164
< cs >
154
0.27
< dragons >
0.05
0.62
< inhibitors >
0.43
2,996
< physicalDamage >
2,749
15,145
< magicDamage >
17,895
3,726
< trueDamage >
803
21,868
< damageDealt >
21,447
30,075
< damageTaken >
21,538
12,067
< goldEarned >
11,589
2.76
< towers >
1.8
0.08
< barons >
0.02
7,600
< heal >
4,044
14,897
< xp >
14,056
17
< visionScore >
21
8
< wardsPlaced >
9
145
< ccTime >
54

How to Counter 诡术妖姬 with 灵罗娃娃 in LoL

The stats provided here underscore some significant 灵罗娃娃 against 诡术妖姬 counter stats that may help us explain the differences between the two. As an example, 灵罗娃娃’s KDA ratio ([kills + assists] / deaths) of NaN is more than 诡术妖姬’s ratio of NaN, showing that 灵罗娃娃 may be more central to her team's team fighting potential than 诡术妖姬..

灵罗娃娃 usually has a slightly smaller longest killing spree than her opponent does. On average, she receives more damage than 诡术妖姬. This commonly reflects differing health capacities, yet it can also show that the one champion has less mobility and thus is unable to escape further harm when poked or engaged.

championDifferences.title

伤害数据

灵罗娃娃
诡术妖姬
物理伤害
魔法伤害
真实伤害

championDifferences.playStyle.title

灵罗娃娃
诡术妖姬

championDifferences.whoIsBetter

Both League champs are great champions. Both have their pros and cons. In the game's current meta, 灵罗娃娃 usually fairs equally well when taking on 诡术妖姬, with a 50.8% win rate. Thus, 灵罗娃娃 makes an ok counter for 诡术妖姬.

While 灵罗娃娃 does have a higher winrate compared to 诡术妖姬, when they face off with one another, 灵罗娃娃 also has a much lower learning curve that makes her a less time consuming champion to learn. You still need to be cautious when picking 灵罗娃娃 into 诡术妖姬.

Additionally, 灵罗娃娃 also has some amount of CC and other utility, a similar amount to 诡术妖姬. This often makes her just as valuable during teamfights, especially when fighting champions with a ton of burst damage.

While there isn't one best champion in League of Legends, in 灵罗娃娃 vs 诡术妖姬 matchups, 灵罗娃娃 is the better champion with a similar win rate, less champion complexity, and a similar amount of utility to help out your teammates during teamfights.

灵罗娃娃 is a decent counter for 诡术妖姬. Make sure you focus your strategy on increasing your CS and taking out objectives. If you do that, you should do very well as 灵罗娃娃 against 诡术妖姬.

additionalInformation.title

method.title2

method.text2

additionalInformation.resources

additionalInformation.readMore

To truly master 灵罗娃娃 to counter 诡术妖姬 during both the lane and mid / late game phases of League of Legends, you should keep reading to learn a few extra lessons on this matchup. If you listen to the build and tips presented here, you will grow your win rate by a lot and be that much closer to League of Legends pro players.

灵罗娃娃 often accumulates a similar amount of CS relative to 诡术妖姬. Champions who typically don't earn many minion kills often don't have to have much CS to be valuable teammates, such as sup champs. They are capable of scaling well off of their abilities and first items alone. Yet, champions with a lot of CS, such as hyper-carries, usually have to have many items to be effective. In either case, try to do better than the values shown on this page to do well.

The ideal items to prioritize in your 灵罗娃娃 versus 诡术妖姬 build consist of 纳什之牙, 裂隙制造者, and 影焰. When 灵罗娃娃 incorporated at least these three pieces in her build, she performed significantly better versus 诡术妖姬 than with most other commonly used builds. In fact, 灵罗娃娃 boasted an average win rate of 50.8% battling 诡术妖姬 with these items in her kit.

To have the greatest likelihood of annihilating 诡术妖姬 as 灵罗娃娃, 灵罗娃娃 players should equip the 征服者, 气定神闲, 传说:欢欣, 坚毅不倒, 复苏之风, and 坚定 runes from the 精密 and 坚决 rune sets. Out of all the rune combinations we have analyed for 灵罗娃娃 vs 诡术妖姬 face-offs, this sequence of runes yielded the best win rate. Notably, these runes averaged a 50.8% winrate overall.

If you would like to get 灵罗娃娃 versus 诡术妖姬 tips and builds for a a specific skill level, please select one from the selection menu shown above. At first, the statistics and build suggestions given are computed using all matches played with both champs.